Learn how to design heat maps in R to enhance your data analysis
Overview
In Detail
R has grown rapidly over the years to become one of the most versatile and valuable tools for data analysis and graphing. One of its many useful features is the heat map representation of numerical data, which is an invaluable tool to discover patterns in data quickly and efficiently.
Instant Heat Maps in R: How-to provides you with practical recipes to create heat maps of all difficulty levels by yourself right from the start. At the end of each recipe, you will find an in-depth analysis that will equip you with everything you need to know to frame the code to your own needs.
Instant Heat Maps in R will present you with all the different heat map plotting functions that exist in R. You will start by creating simple heat maps before moving on to learn how to add more features to them. While you advance step-by-step through the well-connected recipes, you will find out which tool suits the given situation best. You will learn how to read data from popular file formats and how to format the data to create heat maps as well as the ways to export them for presentation.
What you will learn from this book
Approach
Filled with practical, step-by-step instructions and clear explanations for the most important and useful tasks. Heat Maps in R: How-to is an easy to understand book that starts with a simple heat map and takes you all the way through to advanced heat maps with graphics and data manipulation.
Who this book is written for
Heat Maps in R: How-to is the book for you if you want to make use of this free and open source software to get the most out of your data analysis. You need to have at least some experience in using R and know how to run basic scripts from the command line. However, knowledge of other statistical scripting languages such as Octave, S-Plus, or MATLAB will suffice to follow along with the recipes. You need not be from a statistics background.
"synopsis" may belong to another edition of this title.
Sebastian Raschka is a PhD student at Michigan State University and is pursuing a doctorate in Biochemistry and Computer Science. He works in the field of protein structure modeling and is focused on the specificity of protein-ligand interactions. His research involves the development of a protein-ligand docking software based on a novel approach, where he combines the fields of machine learning, pattern recognition, and data mining. In his free time, Sebastian works on web development and uses JavaScript among other technologies to develop web applications that are used by Bioinformaticians and Computational Biologists.
"About this title" may belong to another edition of this title.
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Digital. Condition: New. Filled with practical, step-by-step instructions and clear explanations for the most important and useful tasks. Heat Maps in R: How-to is an easy to understand book that starts with a simple heat map and takes you all the way through to advanced heat maps with graphics and data manipulation. Heat Maps in R How-to is the book for you if you want to make use of this free and open source software to get the most out of your data analysis. You need to have at least some experience in using R and know how to run basic scripts from the command line. However, knowledge of other statistical scripting languages such as Octave, S-Plus, or MATLAB will suffice to follow along with the recipes. You need not be from a statistics background. Seller Inventory # LU-9781782165644
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Digital. Condition: New. Filled with practical, step-by-step instructions and clear explanations for the most important and useful tasks. Heat Maps in R: How-to is an easy to understand book that starts with a simple heat map and takes you all the way through to advanced heat maps with graphics and data manipulation. Heat Maps in R How-to is the book for you if you want to make use of this free and open source software to get the most out of your data analysis. You need to have at least some experience in using R and know how to run basic scripts from the command line. However, knowledge of other statistical scripting languages such as Octave, S-Plus, or MATLAB will suffice to follow along with the recipes. You need not be from a statistics background. Seller Inventory # LU-9781782165644
Quantity: Over 20 available